Prognostics: Design, Implementation, and Challenges

Prognostics is an essential part of condition-based maintenance (CBM), described as predicting the remaining useful life (RUL) of a system. It is also a key technology for an integrated vehicle health management (IVHM) system that leads to improved safety and reliability. A vast amount of research has been presented in the literature to develop prognostics models that are able to predict a system’s RUL. These models can be broadly categorised into experience-based models, data-driven models and physics-based models. Therefore, careful consideration needs to be given to selecting which prognostics model to take forward and apply for each real application. Currently, developing reliable prognostics models in real life is challenging for various reasons, such as the design complexity associated with a system, the high uncertainty and its propagation in the degradation, system level prognostics, the evaluation framework and a lack of prognostics standards. This paper is written with the aim to bring forth the challenges and opportunities for developing prognostics models for complex systems and making researchers aware of these challenges and opportunities

Comparison of different classification algorithms for fault detection and fault isolation in complex systems

Due to the lack of sufficient results seen in literature, feature extraction and classification methods of hydraulic systems appears to be somewhat challenging. This paper compares the performance of three classifiers (namely linear support vector machine (SVM), distance-weighted k-nearest neighbor (WKNN), and decision tree (DT) using data from optimized and non-optimized sensor set solutions. The algorithms are trained with known data and then tested with unknown data for different scenarios characterizing faults with different degrees of severity. This investigation is based solely on a data-driven approach and relies on data sets that are taken from experiments on the fuel system. The system that is used throughout this study is a typical fuel delivery system consisting of standard components such as a filter, pump, valve, nozzle, pipes, and two tanks. Running representative tests on a fuel system are problematic because of the time, cost, and reproduction constraints involved in capturing any significant degradation. Simulating significant degradation requires running over a considerable period; this cannot be reproduced quickly and is costly

Towards design of prognostics and health management solutions for maritime assets

With increase in competition between OEMs of maritime assets and operators alike, the need to maximize the productivity of an equipment and increase operational efficiency and reliability is increasingly stringent and challenging. Also, with the adoption of availability contracts, maritime OEMs are becoming directly interested in understanding the health of their assets in order to maximize profits and to minimize the risk of a system's failure. The key to address these challenges and needs is performance optimization. For this to be possible it is important to understand that system failure can induce downtime which will increase the total cost of ownership, therefore it is important by all means to minimize unscheduled maintenance. If the state of health or condition of a system, subsystem or component is known, condition-based maintenance can be carried out and system design optimization can be achieved thereby reducing total cost of ownership. With the increasing competition with regards to the maritime industry, it is important that the state of health of a component/sub-system/system/asset is known before a vessel embarks on a mission. Any breakdown or malfunction in any part of any system or subsystem on board vessel during the operation offshore will lead to large economic losses and sometimes cause accidents. For example, damages to the fuel oil system of vessel's main engine can result in huge downtime as a result of the vessel not being in operation. This paper presents a prognostic and health management (PHM) development process applied on a fuel oil system powering diesel engines typically used in various cruise and fishing vessels, dredgers, pipe laying vessels and large oil tankers. This process will hopefully enable future PHM solutions for maritime assets to be designed in a more formal and systematic way

State of health estimation of Li-ion batteries with regeneration phenomena: a similar rest time-based prognostic framework

State of health (SOH) prediction in Li-ion batteries plays an important role in intelligent battery management systems (BMS). However, the existence of capacity regeneration phenomena remains a great challenge for accurately predicting the battery SOH. This paper proposes a novel prognostic framework to predict the regeneration phenomena of the current battery using the data of a historical battery. The global degradation trend and regeneration phenomena (characterized by regeneration amplitude and regeneration cycle number) of the current battery are extracted from its raw SOH time series. Moreover, regeneration information of the historical battery derived from corresponding raw SOH data is utilized in this framework. The global degradation trend and regeneration phenomena of the current battery are predicted, and then the prediction results are integrated together to calculate the overall SOH prediction values. Particle swarm optimization (PSO) is employed to obtain an appropriate regeneration threshold for the historical battery. Gaussian process (GP) model is adopted to predict the global degradation trend, and linear models are utilized to predict the regeneration amplitude and the cycle number of each regeneration region. The proposed framework is validated using experimental data from the degradation tests of Li-ion batteries. The results demonstrate that both the global degradation trend and the regeneration phenomena of the testing batteries can be well predicted. Moreover, compared with the published methods, more accurate SOH prediction results can be obtained under this framewor

A rest time-based prognostic framework for state of health estimation of lithium-ion batteries with regeneration phenomena

State of health (SOH) prognostics is significant for safe and reliable usage of lithium-ion batteries. To accurately predict regeneration phenomena and improve long-term prediction performance of battery SOH, this paper proposes a rest time-based prognostic framework (RTPF) in which the beginning time interval of two adjacent cycles is adopted to reflect the rest time. In this framework, SOH values of regeneration cycles, the number of cycles in regeneration regions and global degradation trends are extracted from raw SOH time series and predicted respectively, and then the three sets of prediction results are integrated to calculate the final overall SOH prediction values. Regeneration phenomena can be found by support vector machine and hyperplane shift (SVM-HS) model by detecting long beginning time intervals. Gaussian process (GP) model is utilized to predict the global degradation trend, and nonlinear models are utilized to predict the regeneration amplitude and the cycle number of each regeneration region. The proposed framework is validated through experimental data from the degradation tests of lithium-ion batteries. The results demonstrate that both the global degradation trend and the regeneration phenomena of the testing batteries can be well predicted. Moreover, compared with the published methods, more accurate SOH prediction results can be obtained under this framewor

A simple state-based prognostic model for filter clogging

In today's maintenance planning, fuel filters are replaced or cleaned on a regular basis. Monitoring and implementation of prognostics on filtration system have the potential to avoid costs and increase safety. Prognostics is a fundamental technology within Integrated Vehicle Health Management (IVHM). Prognostic models can be categorised into three major categories: 1) Physics-based models 2) Data-driven models 3) Experience-based models. One of the challenges in the progression of the clogging filter failure is the inability to observe the natural clogging filter failure due to time constraint. This paper presents a simple solution to collect data for a clogging filter failure. Also, it represents a simple state-based prognostic with duration information (SSPD) method that aims to detect and forecast clogging of filter in a laboratory based fuel rig system. The progression of the clogging filter failure is created unnaturally. The degradation level is divided into several groups. Each group is defined as a state in the failure progression of clogging filter. Then, the data is collected to create the clogging filter progression states unnaturally. The SSPD method consists of three steps: clustering, clustering evaluation, and remaining useful life (RUL) estimation. Prognosis results show that the SSPD method is able to predicate the RUL of the clogging filter accurately

Grammaticalisation et transcatégorialité : le verbe qim-le en soureth

This paper develops a morphosyntactic description of a verb of movement and position having a particular functioning in several varieties of Northeastern Neo-Aramaic (NENA). The verb found par excellence in our corpus is that which comes from the root qym “to rise / to stand up”. It works as well alone as predicate of an utterance, as a so-called “auxiliary” verb in a periphrastic structure. It is semantically characterized by a "concrete" meaning denoting a change in positioning. The basic semantism can be subjected to an abstraction process which allows the verb to combine with any verb in an asyndetic construction. It thus functions as an auxiliary. In addition, the semantic abstraction of this verb tends to grammaticalize it more with a discursive function

Efficient Query Processing for SPARQL Federations with Replicated Fragments

Low reliability and availability of public SPARQL endpoints prevent real-world applications from exploiting all the potential of these querying infras-tructures. Fragmenting data on servers can improve data availability but degrades performance. Replicating fragments can offer new tradeoff between performance and availability. We propose FEDRA, a framework for querying Linked Data that takes advantage of client-side data replication, and performs a source selection algorithm that aims to reduce the number of selected public SPARQL endpoints, execution time, and intermediate results. FEDRA has been implemented on the state-of-the-art query engines ANAPSID and FedX, and empirically evaluated on a variety of real-world datasets

Dimensionality Reduction of Quality Objectives for Web Services Design Modularization

With the increasing use of service-oriented Architecture (SOA) in new software development, there is a growing and urgent need to improve current practice in service-oriented design. To improve the design of Web services, the search for Web services interface modularization solutions deals, in general, with a large set of conflicting quality metrics. Deciding about which and how the quality metrics are used to evaluate generated solutions are always left to the designer. Some of these objectives could be correlated or conflicting. In this paper, we propose a dimensionality reduction approach based on Non-dominated Sorting Genetic Algorithm (NSGA-II) to address the Web services re-modularization problem. Our approach aims at finding the best-reduced set of objectives (e.g. quality metrics) that can generate near optimal Web services modularization solutions to fix quality issues in Web services interface. The algorithm starts with a large number of interface design quality metrics as objectives (e.g. coupling, cohesion, number of ports, number of port types, and number of antipatterns) that are reduced based on the nonlinear correlation information entropy (NCIE).The statistical analysis of our results, based on a set of 22 real world Web services provided by Amazon and Yahoo, confirms that our dimensionality reduction Web services interface modularization approach reduced significantly the number of objectives on several case studies to a minimum of 2 objectives and performed significantly better than the state-of-the-art modularization techniques in terms of generating well-designed Web services interface for users.Master of ScienceSoftware Engineering, College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttps://deepblue.lib.umich.edu/bitstream/2027.42/145687/1/Thesis Report_Hussein Skaf.pdfDescription of Thesis Report_Hussein Skaf.pdf : Thesi